Method and System for Analyzing Cable Television Signal Leak Information

ABSTRACT

A method involves identifying a leak location in a cable television system using a detection system, calculating a distance between the leak location and a plurality of shapes or points contained in map data to identify the nearest shape or point, and providing a piece of information corresponding to the nearest shape or point. The piece of information may be a street address or a device.

PRIORITY DATA

This application claims the benefit of U.S. Provisional Application Ser. No. 60/700,935, entitled “METHOD AND SYSTEM FOR DETECTING AND ANALYZING CABLE TELEVISION SIGNAL LEAK INFORMATION,” filed Jul. 20, 2005.

CROSS-REFERENCE

This application is related to U.S. patent application Ser. No. 10/843,798, filed on May 12, 2004, and entitled “METHOD AND SYSTEM FOR AUTOMATICALLY ANALYZING AND MODIFYING CABLE TELEVISION SIGNAL LEAK INFORMATION,” which is a continuation-in-part of U.S. Pat. No. 6,801,162, issued Oct. 5, 2004, and entitled “DOPPLER-BASED AUTOMATED DIRECTION FINDING SYSTEM AND METHOD FOR LOCATING CABLE TELEVISION SIGNAL LEAKS.”

BACKGROUND

Cable television is a system (e.g., a cable “plant”) for delivering television signals to subscribers or viewers by means of coaxial cable. When signals above a certain power level leak from the cable plant into the atmosphere, they may conflict with those used by the aviation industry. Signal leakage can occur in a variety of situations, such as when the shielding of cable cracks or becomes weathered, when connectors become loose, or when the cable breaks.

Rules promulgated by the Federal Communications Commission (FCC) require cable television operators to monitor their cable plants, including their transport media (e.g., cables). Among other items, these rules cover monitoring and reporting on signal “leaks” that occur in the cables. To comply with these standards, cable companies must make power measurements of their facilities and report data obtained during the measurements to the FCC.

Although various methods have been developed to locate cable television leaks, each method presents one or more disadvantages. For example, some methods lack effectiveness in locating or identifying leaks, while others are costly or time consuming.

Accordingly, what is needed is a system and method for accurately locating and identifying leaks.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flow chart of an exemplary method for collecting, processing, and provisioning cable leakage data to an end user.

FIG. 2 is a block diagram illustrating components of an exemplary Doppler-based leak detection system that may be used in the method of FIG. 1.

FIG. 3 is a perspective view of an antenna from the system of FIG. 2.

FIG. 4 is an underside view of the antenna of FIG. 3.

FIG. 5 is a flow chart of an exemplary method for collecting and storing cable leakage data using the leak detection system of FIG. 2.

FIG. 6 is an exemplary computer system that may be used to process and provision data collected using the method of FIG. 5.

FIG. 7 is a flow chart of a data processing method that may be performed using the computer system of FIG. 6.

FIG. 8 is a flow chart of a leak analysis that may be performed by the method of FIG. 7.

FIG. 9 is a flow chart of one method by which radio frequency sources may be assigned symbols by the method of FIG. 7.

FIG. 10 is a flow chart of a Doppler routine that may be performed by the method of FIG. 7.

FIG. 11 is an exemplary screen shot of a work order that may be generated by the method of FIG. 7.

FIG. 12 is an exemplary screen shot of a map that may be generated by the method of FIG. 7.

FIG. 13 is a flow chart of an exemplary method that may be used to modify leak information based on a predefined range value.

FIG. 14 illustrates an exemplary environment within which the method of FIG. 13 may be implemented.

FIG. 15 is a flow chart of an exemplary method that may be used to identify a street address based on a leak location.

FIG. 16 is a flow chart of an exemplary method that may be used to identify a device within a cable television system based on a leak location.

FIG. 17 is a flow chart of an exemplary method that may be used to generate intelligent leak circles.

DETAILED DESCRIPTION

The present disclosure relates generally to detecting cable leakage and, more specifically, to a system and method for locating and identifying cable television signal leaks. It is understood, however, that the following disclosure provides many different embodiments or examples. Specific examples of components and arrangements are described below to simplify the present disclosure. These are, of course, merely examples and are not intended to be limiting. In addition, the present disclosure may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed.

Referring to FIG. 1, in one embodiment, a method 100 illustrates the collection, processing, and provisioning of data that is obtained using a cable leakage detection system. As will be described later in greater detail, the method 100 begins in step 102, where a ride-out is performed. During the ride-out, a vehicle containing the cable leakage detection system traverses a route. The cable leakage detection system automatically stores information about leaks that are detected along the route, such as radio frequency (RF) intensity (e.g., amplitude), location, etc. In step 104, the data is uploaded to a computer for processing.

In step 106, the computer performs data processing operations, which may include performing a leak analysis and/or using Doppler-based calculations to isolate a leak's location. In step 108, work orders may be generated based on the processed data and made available to a user through email, a web page, etc. In addition, street maps may be generated based on the processed data to indicate the locations of leaks. The map generation may include automatically sizing and labeling the maps, and making the maps available to the user. In steps 110 and 112, leak repair data may be uploaded and the work orders associated with the uploaded data may be closed.

It is understood that the method 100 is only one example and that many of the steps may be completed in a different order, and steps may be added or omitted. For example, the method 100 may generate reports using the data and electronically file the reports with the Federal Communications Commission (FCC).

Referring to FIG. 2, one embodiment of a detection system 200, such as may be used in step 102 of FIG. 1, is illustrated. The detection system 200 includes a control unit 202, an antenna unit 204, an automated direction finding (ADF) unit 206, and a Doppler unit 208. The control unit 202, antenna unit 204, ADF unit 206, and Doppler unit 208 may be mounted in a vehicle (not shown). For example, the control unit 202 may be mounted in a docking station 210 in the passenger compartment of the vehicle, with the Doppler unit 208 mounted to the back of the docking station 210. The antenna unit 204 may be secured to the roof of the vehicle, and the ADF unit 206 may be fastened to the antenna unit 204. In the present example, the various components 202, 204, 206, 208 are connected by cables 212, but it is understood that wireless, optical, or other connection means may also be used.

The control unit 202 includes a processor/microcontroller 214, a memory 216, a global positioning system (GPS) unit 218, a user interface 220, a communications interface 222, and an RF meter 224. A bus system 226 may be used to connect the various components 214, 216, 218, 220, 222, 224. The processor 214 is connected to the memory 216, GPS unit 218 (which may be associated with an antenna), user interface 220, communications interface 222, RF meter 224, and Doppler unit 208 (through the docking station 210). The processor 214 receives bearing information from the Doppler unit 208, position information from the GPS unit 218, user input information from the user interface 220, and RF intensity information from the RF meter 224. The processor 214 also stores data in the memory 216. The memory 216 may include permanent memory, removable media (e.g., floppy disks, CD-ROMs, flash cards, etc.), and dynamic memory (e.g., random access memory (RAM)). The communications interface 222 may provide a communications channel between the control unit 202 and the docking station 210. The communications interface 222 may also include components for use in wired or wireless communications with other devices (not shown). Although not shown in detail, the user interface 220 may include buttons, switches, a keypad, a touch screen, or similar interactive controls that let a user interact with the control unit 102, as well as a screen display or other output portion.

The RF meter 224 may be configured to measure signals in a broad spectrum of bandwidths, and may also be configured to display the measured signal strength in a variety of formats. For example, cable television operators generally monitor carrier signals in the frequency bands 108-150 MHz. The RF meter 224 may be configured to monitor the signal strength of carrier signals in these frequency bands. In addition, the RF meter 224 may be configured to calculate signal strength measurements based on the distance between the RF meter 224 and the source of the measured signal. The RF meter 224 or the processor 214 may make adjustments to detected leak levels based on a user defined multiplier that is entered into the control unit 202 through the user interface 220. For example, the control unit 202 may enable the user to indicate a distance from the RF meter 224 to a cable. The distance may be entered or may be selected from a range of distances. The multiplier accounts for the distance, so that selecting a distance of 20 feet results in a multiplier of 2 (e.g., 2× detected leak level). Accordingly, a leak recorded as a 20 would become a leak of 40. Similarly, selecting a distance of 160 would result in the leak being recorded as a 320. This enables the control unit 202 to account for variations in distance between the RF meter 224 and the source of the leak.

It is understood that certain components that are illustrated as being contained in the control unit 202 may be separate components. For example, the GPS unit 218 and the RF meter 224 may both be separate from the control unit 202 and may communicate with the processor 214 via an interface, such as the communications interface 222.

Power to the control unit 202 may be provided from a variety of sources, such as an external direct current source (e.g., a vehicle battery). When the control unit 110 is powered on, a software program is executed by the processor 216, as will be described in greater detail below with reference to FIG. 5.

Referring now to FIG. 3, one embodiment of the antenna unit 204 is illustrated in greater detail. In the present example, the antenna unit 204 comprises a relatively rigid square base 300 that is sixteen and a half inches on each side. The base 300 forms a planar surface with an upper surface 302 and a lower surface 304. Four vertical elements 306, 308, 310, 312 are positioned on the upper surface 302 so that one vertical element is at each corner and oriented perpendicular to the planar surface of the base 300. Each vertical element 306, 308, 310, 312 is the same length, which may be generally between eighteen and twenty-four inches long. The actual length selected for the vertical elements depends on the wavelength of the signals to be detected. For example, each vertical element may be approximately ¼ wavelength of the target signal. Cable RF signals used for signal leakage are generally in the range of 108-150 MHz. As is known in the art, the ¼ wavelength for the 150 MHz signal may be calculated as 11811 inches/150/4=19.685 inches. Accordingly, a length may be selected for the vertical elements 306, 308, 310, 312 that maximizes performance over the desired range of frequencies. Furthermore, the vertical elements 306, 308, 310, 312 may be spaced to avoid undesirable intercoupling, which may occur with a spacing of ⅛ wavelength.

The base 300 includes four corners 314, 316, 318, 320. One of four horizontal elements 322, 324, 326, 328 is attached to each corner and oriented parallel with the planar surface of the base 300. In some embodiments, each corner may be bent upwards or downwards so as to present a small surface that is approximately perpendicular to the planar surface of the base 300. The horizontal elements 322, 324, 326, 328 may then be attached to the small perpendicular surfaces. The horizontal elements 322, 324, 326, 328 serve to extend the size of the base 300 while providing flexibility. For example, if the horizontal elements 322, 324, 326, 328 are each twenty-four inches long, an additional two feet may be added to each side of the base 300, depending on the orientation of the horizontal members. Although more than four horizontal elements may be used, it has been discovered that four horizontal elements are generally sufficient to gather the wavelength and the resulting amplitude.

Because the horizontal members 322, 324, 326, 328 are flexible, they can return to their original position after being displaced. For example, the base 300 may be mounted to the roof of a truck that has a ladder rack on each side. The base 300 may be mounted on one or more “legs” (not shown) that raise the base 300 above the ladder racks. Due to the relatively small footprint of the base 300, not much room is needed. However, the horizontal elements 322, 324, 326, 328 make the base 300 functionally larger and, because they are flexible, they can be displaced by ladders, etc., and return to their original position.

Referring also to FIG. 4, the ADF unit 206 may be attached to the lower surface 304 of the antenna unit 104. The ADF unit 106 includes an ADF antenna board 408 that is contained in a housing 410. The ADF antenna board 408 includes four pin diodes that are connected to the four vertical elements 306, 308, 310, 312 (FIG. 3) via connections 412. The ADF antenna board is also connected to the Doppler unit 208 via a coaxial cable 414 and a multiple conductor wire 416. In operation, the pin diodes may be switched on and off relatively quickly by the Doppler unit 208, enabling the coaxial cable 414 to sequence through the vertical elements 306, 308, 310, 312. In the present example, sixteen points of resolution are provided, with each point representing a direction. It is understood that more points of resolution (e.g., thirty-two or sixty-four) may be used to provide additional directional detail.

Referring now to FIG. 5, a method 500 (representing a software program) may be used by the cable leakage detection system 200 of FIG. 2 to detect and store leakage data. In general, the method 500 “reads” signal bearing information from the Doppler unit 208 (as detected by the antenna unit 204 and ADF unit 206), geographic location information (e.g., longitude and latitude) from the GPS unit 218, and signal strength information (e.g., power) from the RF meter 224. The method 500 then extracts the read information and stores it in a file in the memory 216. In the present example, the information is stored in one of four comma delimited text files. The four files pertain to a range of signal strengths. For example, the four files may pertain to signal strength ranges: (1) 0-19 μV/m; (2) 20-49 μV/m; (3) 50-149 μV/m; and (4) 150 μV/m and up.

After the control unit 202 is powered on, the method 500 controls the reading and storing of information received from the Doppler unit 208, GPS unit 218, user interface 220, and RF meter 224, as well as the display of information through the user interface 220. The storing of information is performed by writing information to the memory 216.

At step 502, the processor 214 of the control unit 202 reads the memory 216 to determine whether a configuration file (not shown) exists on a removable memory device (assuming such a device is present). The configuration file is an editable file that may be used to initialize various parameters of the cable leakage detection system 200. One such parameter may include the default distance between the RF meter 224 and the source of the measured signal. Another such parameter may include a distance at which measurements from the RF meter 224 may be appended with one or more symbols (e.g., a ‘*’, ‘ ’ (a space), ‘<’, or ‘>’) within one of the four comma delimited text files. Each of these symbols is designated as a “DMARK.” The DMARK is used to annotate measurements that are being taken by the RF meter 224, when the meter is set at a high sensitivity threshold. For example, measurements made at distances greater than 100 feet, may read 25 μV/m while the same reading taken at 20 feet may read 5 μV/m. This DMARK can then be imported along with the measured signal into a mapping program for display. If a configuration file exists on the removable memory device, the method 500 proceeds to step 504.

At step 504, the configuration file is read into the memory (RAM) of the control unit 202. The designated parameters associated with the configuration file are then transferred by the processor 214 to the RF meter 224. Upon receipt of the parameters, the RF meter 224 begins measuring the designated frequency, and calculates the power of the designated frequency according to the distance parameter provided. If, at step 502, a configuration file does not reside in the removable memory device, a default configuration file is read, at step 506, from the memory 216 and transferred to the RF meter 224, as above. The method 500 then proceeds to step 508.

At step 508, the processor 214 of the control unit 202 reads the power measurement from the RF meter 224. Typically, this power measurement is in numerical units such as 50 μV/m. The power measurement is based on the distance between the RF meter 224 and the source of the measured signal, and relates to the designated frequency band. The method 500 then proceeds to step 510.

At step 510, a spectral analysis is performed to identify spectral indicators based on the power measurements obtained in step 508. The spectral analysis is designed to determine whether a detected RF signal is from a cable leak (CABLE), a power source (POWER), or noise (INTERFERENCE), such as erroneous RF transmissions. In the present example, the following default values (which may be changed by a user) are in use:

Leak levels (μV/m) 1:200 2:150 3:100 4:50 Search radii (m) 1:200 2:150 3:100 4:50

The spectral analysis may model the physics of a leak because leaks with larger values radiate further than leaks with smaller values. For example, it would be difficult to find a 50 μV/m leak that is close to a 200 μV/m leak, because the 200 μV/m leak would mask the 50 μV/m leak. This relationship is reflected in the spectral analysis. During the spectral analysis, an initial leak parameter is used to identify level 1 leaks (e.g., leaks of 200 μV/m and higher). A 200 meter leak circle (based on the search radii) is drawn with its origin at the source of the highest leak level. It is understood that a leak circle may not actually be drawn, but that a drawn circle is useful for purposes of illustration. Within the leak circle, the data may be analyzed to identify attributes from which spectral indicators may be derived. For example, spectral indicators may be used to identity whether a detected RF signal is from a cable leak, a power source, or noise. For purposes of illustration, the following spectral indicators are used: ‘−’=INTERFERENCE; ‘#’=POWER; ‘+’=CABLE

In the case of power, the data may be analyzed to identify spikes that rise from a noise floor. If a spike is high enough (when compared to a predetermined level), it is assigned the ‘#’ spectral indicator, indicating that the signal is coming from a power source. Similarly, the data may be analyzed to identify video signatures, in which case the source is assigned a ‘+’ spectral indicator. If the data has no identifiable characteristics, it may be assigned a default symbol, such as the ‘−’ spectral indicator. After the spectral analysis is complete, the method 500 continues to step 512.

At step 512, the processor 214 may display the read power measurement via the user interface 220. At this point, a user of the cable leakage detection system 200 can examine a display associated with the user interface 220 to determine the measured signal strength of the designated frequency band. The method 500 then proceeds to step 514, where the processor 214 reads geographical position information from the GPS unit 218. The geographical position information may include such information as longitude, latitude, altitude, and time. The method 500 then proceeds to step 516.

In step 516, the processor 214 receives bearing information from the Doppler unit 208. The Doppler unit 208 may obtain and process bearing information from the antenna unit 204 and ADF unit 206 as follows. In the present example, the Doppler unit 208 rapidly sequences through the pin diodes of the ADF unit 206 and sequentially reads data from each vertical element 306, 308, 310, and 312 of the antenna unit 304. This provides sets of four readings (e.g., data points) that may then be processed by the Doppler unit 208 to provide bearing information based on the strength of the reading from each vertical element 306, 308, 310, and 312. As the antenna unit 204 moves relative to a leak, additional bearing information may be obtained that provides additional information regarding the leak's location through, for example, triangulation.

The method 500 then proceeds to step 518, where the processor 214 stores the power measurement read at step 508, the longitude and latitude geographic information read at step 514, and the bearing information read at step 516, into the memory 216 within the control unit 202. In the present example, the information is stored as a comma delimited text file (e.g., power, longitude, latitude, bearing). The processor 214 then forms a continuous processing loop by proceeding back to step 508. The processing loop, which may include steps 508 through 518, may execute at predetermined intervals, such as once per second. Thus, every second the control unit 202 reads a power measurement from the RF meter 224, geographic information from the GPS unit 218, bearing information from the Doppler unit 208, and stores the power measurement, the longitude and the latitude, and the bearing into a comma delimited text file. This process continues until the control unit 202 is turned off, paused, or until an end command is entered, as discussed below.

The software program embodying the method 500 may include several interrupt routines that are designated as steps 520 through 530. The first, step 520, may be used if the comma delimited text file is stored in temporary memory (e.g., RAM) in step 518 or if a backup copy is to be made. For example, the routine may interrupt the continuous loop of steps 508 through 518 at predetermined intervals (e.g., every two minutes) for the purpose of storing the comma delimited text file into the memory 216 (from RAM) or writing the file to a backup disk, such as a floppy disk. This step provides data backup to the control unit 202 such that if power is lost, no more than two minutes (or another predetermined time interval) of data will be lost.

In some embodiments, the processor 214 may perform processing on the comma delimited text file before storing it. For example, the processing may begin when the processor 214 examines the text file to determine the value of the measured power signal for each second of time. The processor 214 extracts the comma delimited text file into one of the four different text files discussed above according to predefined signal strength criteria. For example, one text file may contain power, longitude and latitude, and bearing for power measurements between 0 and 19 μV/m, a second text file may contain power measurements between 20 and 49 μV/m, a third text file may contain power measurements between 50 and 149 μV/m, and a fourth text file may contain power measurements above 149 μV/m. After extracting the delimited text file into four different text files, the processor 214 may store the files as described. The method 500 then continues the execution loop of steps 508 and 518.

When the processor 214, at step 520, stores the text files, it may first read the memory 216 to determine whether any comma delimited text files already exist. If text files do exist in the memory 216 pertaining to the four signal strength designations, the processor 214 appends the new files onto the preexisting files. Thus, no preexisting files are written over by the processor 214. If no text files exist in the memory 216 during the execution of step 520, the processor 214 creates the files and stores the comma delimited text within them.

A second interrupt, step 522, may occur when a user wishes to change the distance between the RF meter 224 and the measured signal. As described previously, a user may wish to change the distance measurement to provide more accurate power readings depending on the distance to the source of the measured signal. The user enters the desired distance or selects a distance from a predetermined range using the interface 222. Upon receipt, the RF meter 224 calculates the measured power according to the new distance.

A third interrupt, step 524, provides a user with the ability to create other comma delimited text files according to his own criteria. The other text files are termed “flag files” and contain a flag letter (e.g., A, B, or C) as well as longitude, latitude, and bearing. This capability allows a user to log to the memory 216 location information of particular observable information such as a broken cable (flag A), a damaged pedestal (flag B), etc. The files may be created using the user interface 220. The processor 214 stores the flag, along with the most recently read longitude and latitude into a comma delimited text file in the memory 216. The processor 214 may append subsequent flag entries into existing text files in the manner described above.

A fourth interrupt is provided at step 526 which allows a user to end the method 500, and thus end the logging of power measurements to the memory 216. The user can end the method 500, for example, by pressing a key associated with the user interface 220. The key press is transmitted to the processor 214. Upon receipt, the processor 214 stores the existing text files into the memory 216, discontinues reading information from the Doppler unit 208, GPS unit 218, and RF meter 224, and halts program execution. In some embodiments, the control unit 202 may not be able to restart execution until power is turned off and then back on.

A fifth interrupt is provided at step 528 that allows a user to start, pause, or restart the method 500 from the user interface 220. For example, the user may toggle between program execution and program pause by pressing one or more keys associated with the user interface 220. If the method 500 is already being executed, pressing the key may cause the method to pause or suspend execution.

A sixth interrupt may provided at step 530 that allows a user to set the speed at which power, position, and bearing information are read from the RF meter 224, GPS unit 218, and Doppler unit 208, and stored in the memory 216. The speed may be entered via the user interface 220 by entering a desired time interval or by selecting a time interval from a predetermined range. The processor 214 then logs data at a rate corresponding to the entered speed.

In addition to the above interrupts, a supervisory interrupt (not shown) may be provided that produces an error log of particular error conditions that may occur within the control unit 202. For example, an error condition may result from the failure of any one of the RF meter 224, GPS unit 218, Doppler unit 208, or user interface 220 to communicate with the processor 214 within the control unit 202. The error log may be a text file that details the nature of the error and is stored in the memory 216.

Referring now to FIG. 6, in another embodiment, an exemplary computer 600, such as may utilize leakage data collected using the method 500 of FIG. 5, is illustrated. The computer 600 may include a central processing unit (“CPU”) 602, a memory unit 604, an input/output (“I/O”) device 606, and a network interface 608. The components 602, 604, 606, and 608 are interconnected by a bus system 610. It is understood that the computer may be differently configured and that each of the listed components may actually represent several different components. For example, the CPU 602 may actually represent a multi-processor or a distributed processing system; the memory unit 604 may include different levels of cache memory, main memory, hard disks, and remote storage locations; and the I/O device 606 may include monitors, keyboards, and the like.

The computer 600 may be connected to a network 612. Because the computer 600 may be connected to the network 612, certain components may, at times, be shared with other computers and digital devices 614. Therefore, a wide range of flexibility is anticipated in the configuration of the computer. Furthermore, it is understood that, in some implementations, the computer 600 may act as a server to other computers 614.

Referring now to FIG. 7, in another embodiment, a method 700 illustrates using the computer 600 of FIG. 6 to process data that was collected using the method 500 of FIG. 5. In the present example, the computer 600 is a server and may be accessed by other computers 614. In step 702, data is uploaded to the server 600 for processing. The data may be uploaded to the computer server in a variety of ways. For example, the data may be transferred from the control unit 202 to a computer (e.g., the computer 614) using removable media (e.g., a floppy disk or flash card), by wireless transfer (e.g., Nextel, CDPD, or GSM/GPRS), by a cable (e.g., a serial cable), or by interfacing the control unit 202 with a docking station connected to the computer 614. The computer 614 may then transfer the data to the server 600. In some embodiments, each detection system 200 may be associated with a unique identifier that may be used by the server 600 to identify the source of the uploaded data. Accordingly, a user may initiate an upload procedure by pressing a key associated with the user interface 220 of the control unit 202, at which time a client program residing on the computer 614 will retrieve the data from the memory 216, transfer the data to the server 600, store a backup of the data in the computer 614's memory, and delete the files from the memory 216.

In step 704, the uploaded data is processed. Exemplary processing may include leak analysis (FIGS. 8 and 9) and the execution of Doppler routines on the data (FIG. 10).

Referring also to FIG. 8, a method 800 illustrates the leak analysis of step 704 in greater detail. Once the data is uploaded to the server 600, a leak analysis may be initiated that performs a logical search through the data. In the present example, the following default values (which may be changed by a user) are in use:

Leak levels (μV/m) 1:200 2:150 3:100 4:50 Search radii (m) 1:200 2:150 3:100 4:50 The leak analysis may model the physics of a leak because leaks with larger values radiate further than leaks with smaller values. For example, it would be difficult to find a 50 μV/m leak that is close to a 200 μV/m leak, because the 200 μV/m leak would mask the 50 μV/m leak. This relationship is reflected in the leak analysis.

In steps 802 and 804, the method 800 begins with an initial leak parameter and identifies level 1 leaks (e.g., leaks of 200 μV/m and higher). In step 806, a 200 meter leak circle (based on the search radii) is drawn with its origin at the source of the highest leak level. It is understood that a leak circle may not actually be drawn, but that a drawn circle is useful for purposes of illustration. The method 800 then proceeds to step 808, where symbols are derived based on spectral indicators (such as those assigned in step 510 of FIG. 5), as is illustrated in greater detail in FIG. 9.

Referring also to FIG. 9, a method 900 assigns symbols based on a previous spectral analysis. It is understood that the spectral analysis may be performed as part of the present step if desired. The symbols are designed to indicate whether a detected RF signal is from a cable leak (CABLE), a power source (POWER), or noise (INTERFERENCE), such as erroneous RF transmissions. The leak analysis, using the results of the method 900 and the previously determined amplitudes and spectral indicators, produces a point file (e.g., a data set) that includes an amplitude, a symbol type, and a spectral indicator for each leak. In the present example, the following indicators and symbols are used:

Spectral indicators: ‘−’=INTERFERENCE; ‘#’=POWER; ‘+’=CABLE

Symbols: circle=INTERFERENCE; triangle=POWER; square=CABLE

The symbol (circle, triangle, or square) is selected as follows. In step 902, a determination is made as to whether all the spectral indicators inside the leak circle are ‘−’. If yes, the method 900 proceeds to step 904, where the INTERFERENCE symbol (circle) is selected. This is the only time the INTERFERENCE symbol is created. If no, the method 900 continues to step 906, where a determination is made as to whether there are more ‘+’ or ‘#’ spectral indicators in the leak circle. The symbol is selected based on a majority, so the POWER symbol (triangle) will be selected if the majority of the spectral indicators are ‘#’ (step 908), and the CABLE symbol (square) will be selected if the majority of the spectral indicators are ‘+’ (step 910). No majority (e.g., a tie) results in the selection of the CABLE symbol (step 910).

Referring again to FIG. 8, after assigning the symbols based on the spectral indicators, the method 800 continues to step 810, where the street address that is nearest to the highest identified leak level is selected. In step 812, all the data points in the leak circle are removed except the highest identified leak level. In step 814, a determination is made as to whether all of the iterations have been performed (e.g., whether leaks have been identified using the predefined parameters). If not, the method 800 proceeds to step 816, where the next leak parameter is selected. The method 800 then returns to step 804 and identifies leaks, performs spectral analysis, etc., as previously described with respect to steps 804-814. This enables the method 800 to identify and label smaller leaks that were covered by the highest identified leak level. After the leak analysis is completed, the method 800 ends and the method 700 of FIG. 7 may execute a Doppler routine, as is described in greater in detail with reference to FIG. 10.

Referring now to FIG. 10, a method 1000 uses bearing information collected via the Doppler unit 208 to more accurately characterize a leak. Although the method 1000 is illustrated for purposes of clarity as a method separate from the leak analysis method 700 of FIG. 7, it is understood that the method 1000 may be integrated into the method 700.

Doppler based data may be used to overcome problems associated with determining a source of the leak. For example, when a vehicle is on a ride-out, it is difficult to calculate the actual distance from the vehicle to the cable. One way to do this is to use an estimated range, as was described above with respect to FIG. 5. Another way is to incorporate Doppler data, as this allows such benefits as a triangulation. However, one problem with Doppler based data stems from reflected signals (e.g., multi path). These reflected signals may be detected, even though they are erroneous. Multi path may affect both the amplitude of RF leakage levels and the calculated location of the leaks. As will be described below, the negative effect of multi path may be overcome while processing the bearing data.

In step 1002, all bearings for each measured leak are identified. In step 1004, lines are “drawn” (e.g., calculated) out from each measured leak using the bearing information. For example, if bearing information is taken on a single leak once a second for three seconds, there would be three lines drawn from the leak. In steps 1006 and 1008, points of intersection are determined for the lines associated with each leak and, if a line does not match, it is rejected as being the result of multi path. In some embodiments, a range of intersecting lines may be averaged during the processing. For example, one line that is twenty feet from a point may be averaged with another line that is forty feet from the point to produce a single line that is thirty feet from the point.

In step 1010, the distance to the leak can be calculated using triangulation. The calculated distance may then be used to alter the multiplier for that leak to more accurately identify the amplitude of the leak. For example, a leak detected at 4 μV/m with a calculated distance of 80 feet would be identified as a 32 μV/m leak.

The bearing information may also be examined to identify patterns that provide additional details regarding a leak. For example, a leak may be in a cable located at the back of a house, rather than on a pole. During a ride-out, RF signals from the leak may be detected when the detection system 200 is positioned on the road between the house where the leak occurs and a neighboring house, but may be blocked when a house is between the detection system 200 and the leak. Accordingly, data representing the leak will exist for the time the leak is detected (from between the houses), but there will be no data for the positions on either side of the leak (where a house is blocking the leak from being detected). Therefore, by examining the data for a general pattern (such as NULL, leak data, NULL), it may be determined that the leak is at the back of a house, rather than on a pole. Other patterns may be used to identify similar information.

It is understood that the bearing information may be used in addition to the distance information gathered with respect to FIG. 5 (e.g., as a check) or may replace the distance data entirely. After the leaks are processed using the Doppler routine, the method 1000 ends and the method 700 of FIG. 7 continues to step 706.

Referring again to FIG. 7 and also to FIG. 11, work orders may be generated in step 706 based on the processing of step 704. Referring specifically to FIG. 11, a work order 1100 may include location information 1102, amplitude of the leak 1104 (which may be corrected using Doppler data as described with respect to FIG. 10), and additional information. In some embodiments, the work order may be emailed to a technician and/or may be viewed as a web page provided by the server 600.

Referring again to FIG. 7 and also to FIG. 12, maps and associated information may be generated in step 708. Referring specifically to FIG. 12, a map screen 1200 illustrates a map 1202 of a leakage area may be generated by superimposing the processed data onto a digital map by latitude and longitude. For example, the latitude and longitude of the work order of FIG. 11 may be used to place the leak onto the map of FIG. 12, along with an associated symbol 1206 as described above (e.g., a square for a cable leak). A circle 1208 may be drawn around each leak to indicate the amplitude of the leak or other information. Flag information (e.g., to indicate a broken wire or a damaged pedestal) may also be indicated on the map or in a comments section. Another map 1204 may reproduce the general area of which the map 1202 is a part. It is understood that the view of the map may be adjustable (e.g., zoomed in or out), and that other known map techniques may be used to alter the map as desired.

Other functionality may be incorporated into the method 700 as desired. For example, a user may access a map or list of ride-outs, along with leaks that were detected during each ride-out. A user may also define leak parameters that are used for processing the data, as well as flags and other information. In addition, the method 700 may be used to generate summaries, reports, or other compilations of data to enable users to more accurately estimate repair costs, equipment upgrades, personnel needs, and perform other planning tasks. Furthermore, the method 700 may incorporate the data into a report, such as is required by the FCC, and automatically file the report.

Referring now to FIG. 13, in still another embodiment, a method 1300 illustrates the use of predefined range information with the collection, processing, and provisioning of data that is obtained using a cable leakage detection system. As previously described, in some embodiments, a user may make adjustments to a control unit (e.g., the control unit 202 of FIG. 2) to indicate a distance from an RF meter to a cable. The method 1300 enables the control unit (and/or the computer 600) to automatically adjust the recorded leak magnitude to account for variations in distance between the RF meter and the source of the leak. In the present embodiment, distance variations may be handled without user intervention by applying one or more dynamically identified and/or predefined range values. The method 1300 may be contained within and executed by the cable leakage detection system 200, another computer (e.g., the computer 600 of FIG. 6), or may be distributed between multiple processing devices. For example, portions of the method 1300 may be executed by the cable leakage detection system 200 (e.g., the leak detection), while other portions may be executed by the computer 600 (e.g., further processing of the leak information). Furthermore, portions of the method 1300 may be stored on one device and executed on another device.

In step 1302, a leak location may be identified in a cable system as previously described. In step 1304, a range value may be identified. In some embodiments, this range value may be selected from a set of predefined values that are used to define a distance from a point on the cable system to the cable leakage detection system. For example, the cable leakage detection system may be in a vehicle on a nearby road, and each distance may indicate the distance from the cable system to the road. In other embodiments, the range value may be dynamically identified (e.g., using a Doppler system to identify the leak location using triangulation). In still other embodiments, a combination of predefined and dynamic range values may be used. For example, a Doppler system may be used to triangulate the leak location, and the Doppler identified location may be used to identify a nearest predefined range value. Accordingly, is it understood that the range value may be identified using a number of different techniques or a combination of such techniques, and that each technique may use predefined and/or dynamically identified information.

In step 1306, the leak magnitude may be modified based on the range value. For example, the leak magnitude may be scaled as previously described with respect to the operation of the control unit 202 and the second interrupt (step 522) of the method 500. Accordingly, the leak magnitude may be corrected based on the predefined distance information. It is understood that some embodiments may include determining whether such a modification is needed. For example, a scaling value associated with the range value may be checked to determine whether the leak magnitude needs to be modified, and the modification may occur only if the check indicates that the leak magnitude needs to be scaled (e.g., if the distance indicates that the detected leak magnitude is not correct).

The predefined range values may be provided in multiple ways. For example, a user may directly input this information, or previously collected rideout data may be used to automatically extrapolate previously input distance values (e.g., from step 522 of the method 500).

It is understood that the term “range value” is used to represent many possible values that may be used in the method 1300. For example, a range value may include longitudinal/latitudinal coordinates, and the distance itself may be calculated using the range value and the cable leakage detection system's longitudinal/latitudinal coordinates. In such an embodiment, the range value's coordinates may be predefined, rather than the distance itself. In other embodiments, the range value may be a scaling factor (e.g., 4). In some examples, multiple sets of range values may be used. For example, a first set of range values may be used to identify cable plant locations that are associated with a line, while a second set of range values may be used to identify cable plant locations that are associated with buildings. In other examples, a range value may have additional information associated with it that negates the need for multiple sets of range values (e.g., a distance and a line/building identifier).

With additional reference to FIG. 14, an exemplary map 1400 illustrates one possible environment within which the method 1300 may be implemented. The map 1400 illustrates a cable system 1402 running along a street 1404. A house 1406 is connected to the cable system, and a vehicle carrying a cable leakage detection system 1408 is on the street 1404. Various map layers may be associated with (e.g., superimposed on) the map 1400, such as layers for streets, utilities, and additional map layers, including a first map layer containing predefined range values 1410 a-1410 f and a second map layer containing a predefined range value 1412. It is understood that the map layers may not be visible map layers of the map 1400, but may represent data that can be used in conjunction with the map. For example, the range values may be associated with map grid coordinates, longitudinal/latitudinal information, etc., for positioning purposes.

A user may directly input the range values into the appropriate map layer using, for example, a utility (e.g., a software program) designed for this purpose or a map editing tool. Alternatively or additionally, a utility may be used that processes previously collected rideout data, automatically extrapolates the range values from previously input distance values, and enters them into the appropriate map layer. Furthermore, compiled location data (e.g., from a cable company responsible for the cable system) may be used to provide the map overlay information.

In the present example, each predefined range value defines an approximate distance from the corresponding point on the cable system 1402 to the cable leakage detection system 1408 (assuming that the detection system is on a certain area on the street). For example, the range value 1410 e defines a distance 1414. The range value 1412 defines a distance (or a range of distances) from the house 1406 to the cable leakage detection system 1408 (if the cable leakage detection system was in front of the house).

As is described in greater detail in the following paragraph, it is understood that the range values may not be evenly spaced along the cable system 1402. For example, one or two range values may be used to indicate a portion of the cable system that is twenty feet from the street, while another range value may be used to indicate a point where the cable system is ten feet from the street. In other embodiments, many range values may be supplied to provide a more accurate representation of the position of the cable system.

In the present embodiment, the street 1404 is divided into multiple street segments (not shown). Each street segment is a line segment with a beginning point and an ending point connected by a line. In general, the more curved the street 1404, the more street segments will be needed to accurately represent the street. Each street segment may contain data, such as the name of the street and the address range of that portion of the street (e.g., addresses beginning at 100 or 101 and ending at 198 or 199). Each range value may be associated with one of the street segments. As the cable system 1402 changes its range from the street, each street segment will have the correct changing range value.

In some embodiments, a triangulation process (as described above) may be used to provide alternative or additional positioning information about a leak location. For example, triangulation may be used to more accurately locate the leak, which may result in more accurate distance information.

Referring again to FIG. 13 and with continued reference to FIG. 14, the method 1300 may be applied to the environment of FIG. 14 as follows. The method 1300 begins in step 1302 by locating a leak location. For purposes of example, the leak location is near the range value 1410 e and the cable leakage detection system 1408 is at the position shown. Accordingly, the distance 1414 separates the leak location and the detection system.

In step 1304, the range value 1410 e is identified and the distance 1414 is obtained (e.g., by retrieving a predefined distance or by calculating the distance using coordinates). To identify the range value 1410 e, a decision may be made as to which of the first and second map layers should be used. For example, the decision may be based on historical leak statistics from the cable system to determine whether most of the previously reported leaks were located in the house or the line. This information may then be used to determine which map layer (and corresponding range values) should be used. Although the present example uses the predefined range value 1410 e, it is understood that the range value may be dynamically calculated or based on dynamically calculated information. For example, a triangulation process using the previously described Doppler system may be used to identify the leak location, which may then be used to more accurately identify or verify the range value 1410 e.

In step 1306, the leak magnitude may be modified based on the distance. For example, if the distance is twenty feet, the leak magnitude may be multiplied by two. Accordingly, the method 1300 enables leak information to be automatically manipulated without requiring constant human intervention.

In other embodiments, geocoded range values may be used for other purposes. For example, such range values may be used as part of a vehicle tracking system, with a path of a vehicle and other information (e.g., a time stamp) appearing on a map or printout. Such range values may also include or be used in conjunction with GPS information. Accordingly, the use of such predefined range values may be applied to many different situations.

Referring now to FIG. 15, in still another embodiment, a method 1500 illustrates the use of data (e.g., AutoCad data) representing maps that are in flat Cartesian coordinates to identify actual street addresses or house numbers based on a leak location that was provided in a spherical GPS format. The method 1500 may be implemented by a software program. In the past, mapping problems have existed due to the use of data representing maps that are in flat Cartesian coordinates. As such, the maps do not translate in environments such as the spherical GPS/GIS (Geographical Information System) environment without first converting the data. The method 1500 begins with step 1510 in which a leak location is identified in a cable television system using a detection system. The leak location is identified by the methods and systems previously discussed in FIGS. 1-14. Alternatively, the leak location may be identified by other methods and systems well known in the art. The leak location is typically provided in the spherical GPS environment.

In step 1520 a, the map data (e.g., AutoCad data) that is in the flat Cartesian coordinate environment is converted with a geographical converter such as ArcInfo or ArcView software. The map data includes a plurality of polygons that represent the lots of homes with lot lines, and each lot has an actual street address or home number. However, the map data may alternatively be provided as a point file in which a single point represents a single street address. It is understood that the map data may be provided in other formats that may also be converted to the spherical GPS environment. Optionally, in step 1520 b, the method 1500 may be implemented by converting the leak location (instead of the map data) from the spherical GPS environment to the flat Cartesian coordinate environment. It is contemplated that other types of positioning formats may be utilized. The geographical converter is configured to convert data from the flat Cartesian coordinate environment to the spherical GPS environment, or vice versa.

In step 1530, a distance is calculated between the leak location and a plurality of polygons contained in map data to identify the nearest polygon to the leak location. This is possible since the leak location and the plurality of polygons in map data are both in the same environment. However, if the map data was provided as a point file, then the closet point to the leak location would be identified. In step 1540, the street address corresponding to the nearest polygon (or point) to the leak location is provided using the map data. For example, the street address corresponding to the nearest polygon (or point) is 9696 Maple Ave. In step 1550, a leakage schematic is generated by superimposing the leak location with the converted map data that contains the street address of the nearest polygon (or point) as well as all the street addresses of the other polygons (or points) within that area. Furthermore, work orders may be generated based on the processed data and made available to a user through email, a web page, etc. It is understood that the lots of homes and their corresponding street addresses may be configured in other shapes such as circles.

Referring now to FIG. 16, in another example, a method 1600 illustrates how to identify a closest piece of cable equipment to a leak location using a customers' map data (e.g. AutoCad data) containing their cable system design. The method 1600 may be implemented by a software program. The customers' map data of their cable system design is typically in a flat Cartesian coordinate environment. The method 1600 begins with step 1610 in which a leak location is identified in a cable television system using a detection system. The leak location is identified by the methods and systems previously discussed in FIGS. 1-14. Alternatively, the leak location may be identified by other methods and systems well known in the art. The leak location is typically provided in the spherical GPS environment.

In step 1620 a, the customers' map data containing the cable system design that is in the flat Cartesian coordinate environment is converted with a geographical converter such as ArcInfo or ArcView software. The devices are typically represented by a point file in which a single point corresponds to a single device. The cable system design includes devices such as taps and amplifiers. However, the devices may alternatively be represented by other shapes such as a polygon or a circle. Optionally, in step 1620 b, the method 1600 may be implemented by converting the leak location (instead of the customers' map data) from the spherical GPS environment to the flat Cartesian coordinate environment. The geographical converter is configured to convert data from the flat Cartesian coordinate environment to the spherical GPS environment, or vice versa. It is contemplated that other types of positioning formats may be utilized.

In step 1630, a distance is calculated between the leak location and a plurality of points contained in the customers' map data to identify the point that is closest to the leak location. This is possible since the leak location and the plurality of points in map data are both in the same environment. However, if the devices are represented by polygons or other suitable shapes, then the distance is calculated to find the closest polygon or other suitable shape. In step 1640, the device corresponding to the closet point (or polygon) is provided as a probable cause of the leak. For example, the device corresponding the closest point (or polygon) may be a 23 value tap or a line extender amplifier. In step 1650, a leakage schematic is generated by superimposing the leak location on the customers' converted map data that contains the identified device in the cable system design. Furthermore, the leakage schematic may also include lots of homes and their street addresses as described in FIG. 15. Additionally, work orders may be generated based on the processed data and made available to a user through email, a web page, etc.

Referring now to FIG. 17, in still another embodiment, a leak analysis (L.A.) method 1700 illustrates generating intelligent leak areas from leakage data collected in a cable television system. In the present embodiment, the intelligent leak areas are circles. The L.A. method 1700 may be implemented by a software program. The L.A. method 1700 begins with step 1710 in which a plurality of leakage readings are obtained. The plurality of leakage readings are obtained by the methods and systems described in FIGS. 1-14. However, the plurality of leakage readings may alternatively be obtained by other methods and systems well known in the art. In the present embodiment, the L.A. method 1700 inspects the plurality of leakage data with four sweeps through the data to generate four different intelligent leak circles. It is understood that the number of intelligent leak circles will depend on the plurality of leakage readings.

In step 1720, a first leak circle is calculated around a first leak location resulting from a first sweep through the plurality of leakage readings. The parameters of the L.A. method 1700 are defined as power levels and leak radii. For example, the default power levels in descending order are 200, 150, 100, and 50 μV/m. The corresponding defaults for the leak radii are 200, 150, 100, and 50 meters, respectively. The first leak circle is calculated by taking all leakage readings that are greater than or equal to 200 μV/m and using a 200 meter circle that originates from the highest reading in that cluster of leakage readings. Then all leakage readings within the first circle except for the highest are discarded. The lower leakage readings within the first circle are the product of standing waves from that highest reading. Thus, discarding the lower level readings prevents the L.A. method 1700 from listing leaks that would be duplicates of the highest reading.

In step 1730, a second circle is calculated around a second leak location resulting from a second sweep of the plurality of leakage readings. The second circle is calculated by taking all the leakage readings ranging from 150 to 199 μV/m that were not included in the first circle and using a 150 meter circle that originates from the highest reading in that cluster of leakage readings. Then all leakage readings within the second circle except for the highest are discarded. The lower leakage readings within the second circle are the product of standing waves from that highest reading. Thus, discarding the lower level readings prevents the L.A. method 1700 from listing leaks that would be duplicates of the highest reading.

In step 1740, a third circle is calculated around a third leak location resulting from a third sweep of the plurality of leakage readings. The third circle is calculated by taking all the leakage readings ranging from 100 to 149 μV/m that were not included in the first or second circle and using a 100 meter circle that originates from the highest reading in that cluster of leakage readings. Then all leakage readings within the third circle except for the highest are discarded. The lower leakage readings within the third circle are the product of standing waves from that highest reading. Thus, discarding the lower level readings prevents the L.A. method 1700 from listing leaks that would be duplicates of the highest reading.

In step 1750, a fourth circle is calculated around a fourth leak location resulting from a fourth sweep of the plurality of leakage readings. The fourth circle is calculated by taking all the leakage readings less than or equal to 99 μV/m that were not included in the first, second, or third circle and using a 50 meter circle that originates from the highest reading in that cluster of leakage readings. Then all leakage readings within the fourth circle except for the highest are discarded. The lower leakage readings within the fourth circle are the product of standing waves from that highest reading. Thus, discarding the lower level readings prevents the L.A. method 1700 from listing leaks that would be duplicates of the highest reading. It is understood that all of these parameters such as the number of sweeps, the range of power levels, and the leak radii are variables that can be defined by the user of the software program.

The L.A. process is effective in that it keeps a ride out technician from looking for leaks that are radiating over several streets. It is very inefficient to manually look for a leak that is not on the same street as the technician. The L.A. method 1700 also keeps in mind the physics of RF leakage in that a smaller leak cannot be found if it is masked by a larger leak. Therefore, throwing out all the leakage readings except the highest in a leak circle is the correct and logical way to treat the leakage data. If a smaller leak is inside the circle of a larger leak, it can only be found after the larger leak is repaired. Accordingly, each search focuses only on readings not discarded in the previous search.

In step 1760, a database is generated from the leak circles (including its corresponding leak locations) that were determined above. The database can be made aware of other Wavetrackers (or equipment that combines GPS and RF leakage data) patrolling the same area. For example, if another Wavetracker detects a leak that falls inside of a previously discovered leak location and its corresponding leak circle, it will not be treated as an additional leak. This may be applied to data found the same day or in following days. In step 1770, a determination is made on whether any of the original leaks (highest readings of the leak circles) have been repaired. If the original leaks have been repaired, the database is updated with the most recent data or new data (from that same area) that is processed in the same manner as described in steps 1710 to 1760. The leak circles will keep any leak found in its proximity from being produced into a duplicate leak until the original leak is repaired and cleared out from the database. If the original leak has not been repaired, in step 1780, a leakage schematic is generated by superimposing the leak locations and circles on map data of that area in preparation for repairs.

Even though the method 1700 is described utilizing leak circles, it is understood that the use of the circle only defines an area surrounding the highest leakage reading. The importance of this area is to prevent duplicate leakage information and to provide more efficiency for analyzing and repairing leaks in a cable television system as described in detail above. Accordingly, other shapes such as triangles, squares, other polygons, irregular shapes, or any other enclosed shape may be used to define the area surrounding the highest leakage reading.

In still another example, leakage schematics may be provided based on the methods described in FIGS. 15-17. More specifically, based on the identification of the nearest device and nearest lot lines (street addresses), a schematic of each leak is provided. For example, a circle (leak radius) that surrounds the highest leakage reading in a cluster of leaks is provided. A closeup of each leak that shows the immediate proximity of that RF leak may be provided that includes such features as lot lines, taps, and amplifiers. This may be especially helpful in areas where the cable plant is underground (in pedestals) or hard to find behind bushes and trees.

While the preceding description shows and describes one or more embodiments, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the present disclosure. For example, although a server is used to describe various embodiments of the present disclosure, another computer or other digital device could also be used. In addition, LORAN or other positioning techniques may be used. Also, other mapping approaches may be utilized as disclosed in detail in U.S. Pat. No. 5,294,937, entitled “CABLE LEAKAGE MONITORING SYSTEM” and assigned to the same assignee as the present disclosure, and hereby incorporated by reference as if reproduced in its entirety. Therefore, the claims should be interpreted in a broad manner, consistent with the present disclosure. 

1. A computer-executable method for identifying a piece of information corresponding to radio frequency (RF) leak information in a cable television system, the method comprising: identifying a leak location in the cable television system using a detection system; calculating a distance between the leak location and a plurality of shapes contained in map data to identify the nearest shape; and providing the piece of information corresponding to the nearest shape.
 2. The computer-executable method of claim 1, wherein the providing includes configuring the piece of information to include a street address or device within the cable television system.
 3. The computer-executable method of claim 2, wherein the device includes a tap or amplifier.
 4. The computer-executable method of claim 3, wherein the calculating includes configuring the plurality of shapes to include a plurality of polygons.
 5. The computer-executable method of claim 4, further comprising generating a leakage schematic and work order that includes the leak location and street address or device corresponding to the nearest polygon.
 6. The computer-executable method of claim 5, wherein the nearest polygon includes lot lines of the street address.
 7. The computer-executable method of claim 6, further comprising converting the plurality of polygons contained in map data with a geographical converter, wherein the geographical converter converts the plurality of polygons contained in map data from a flat Cartesian coordinate environment to a spherical Global Positioning System (GPS) environment.
 8. The computer-executable method of claim 6, further comprising converting the leak location with a geographical converter, wherein the geographical converter converts leak location from a spherical GPS format to a flat Cartesian coordinate format.
 9. A computer-executable method for identifying a piece of information corresponding to radio frequency (RF) leak information in a cable television system, the method comprising: identifying a leak location in the cable television system using a detection system; calculating a distance between the leak location and a plurality of points contained in map data to identify the closest point; and providing the piece of information corresponding to the closest point.
 10. The computer-executable method of claim 9, wherein the providing includes configuring the piece of information to include a street address or device within the cable television system.
 11. The computer-executable method of claim 10, wherein the device includes a tap or amplifier.
 12. The computer-executable method of claim 11, further comprising generating a leakage schematic and work order that includes the leak location and the street address or device corresponding to the closest point.
 13. The computer-executable method of claim 12, further comprising converting the plurality of points in map data with a geographical converter, wherein the geographical converter converts the plurality of points in map data from a flat Cartesian coordinate format to a spherical GPS format.
 14. The computer-executable method of claim 12, further comprising converting the leak location with a geographical converter, wherein the geographical converter converts leak location from a spherical GPS format to a flat Cartesian coordinate format. 15-21. (canceled) 